Février 2023

Bonjour, j’espère que tout le monde va bien. Voici les nouveautés du mois de février. John Myles-White a demandé à ChatGPT son avis sur Julia et voici ce que cela donne. Je me suis aussi aperçu furtivement dans cette vidéo ^_^

Billets de blog¶

• CUDA.jl 4.0

• Using Measurements.jl for Triangulation in Julia

• Abstraction In Julia Vs. Abstraction In Python: A Quick Comparison

• Grand Julia containers test. Can you get a perfect score?

• oneAPI.jl 1.0: oneMKL, Intel Arc and Julia 1.9

• Adjusting to Julia: Generating the Fibonacci sequence

• Adjusting to Julia: The Levenshtein algorithm

• Adjusting to Julia: Tea tasting

• Julia macros for beginners

• Julia and Python better together

• Julia Boards the Titanic- A brief introduction to the MLJ.jl package

• Z3.jl - Optimization Examples Solved with Julia

• Bifurcation plot of an ordinary differential equation model using a brute force approach

• What is ∈ in Julia?

Packages¶

• MultiObjectiveAlgorithms.jl: Collection of algorithms for multi-objective optimization.

• BridgeStan.jl: efficient in-memory access through Python, Julia, and R to the methods of a Stan model.

• CamiMath.jl: Mathematics library with integer-overflow protection.

• Tidier.jl: Julia implementation of the R tidyverse mini-language.

• PairPlots.jl: Beautiful and flexible vizualizations of high dimensional data.

• Delaunator.jl: Library for Delaunay triangulation of 2D points.

• Polymers.jl: Polymers Modeling Library.

• PredefinedDynamicalSystems.jl: Collection of predefined dynamical systems for DynamicalSystems.jl.

• SymbolicRegression.jl/: Distributed High-Performance symbolic regression in Julia.

• GenLinearAlgebra.jl: Linear algebra on an arbitrary field or ring.

• TinyKernels.jl: Tiny abstraction for GPU kernels, currently supporting CUDA (Nvidia) and ROCm (AMD) backends.

• DiffusionMap.jl: Diffusion maps for non-linear dimensionality reduction / manifold learning.

• CategoricalMonteCarlo.jl

• StaticArrayInterface.jl: Interface designs for enforcing static computations in array functions with Julia.

• Survey.jl: Analysis of complex surveys.

• ClusterDepth.jl: Fast implementation of the ClusterDepth multiple comparison algorithm from Frossard and Renaud.

• ThreeBodyProblem.jl: An astrodynamics package for working in the three body problem.

• UnitParser.jl: Simple units parser for julia.

• SymbolicGA.jl: Geometric algebra transformations at compile-time.

• ConformalPrediction.jl: Predictive Uncertainty Quantification through Conformal Prediction for Machine Learning models trained in MLJ.

• SeparableFunctions.jl: Calculates multidimensional functions faster by exploiting their separability.

• Xicor.jl: An implementation of the Xi Correlation coefficient and hypothesis test.

• SingleCellProjections.jl: Analysis of Single Cell Expression data in Julia.

• AlgebraicInference.jl: Compositional Bayesian inference.

Vidéos¶

• From Mesh Generation to Adaptive Simulation: A Journey in Julia

• Machine learning with Julia and Flux

• Introduction to Control Analysis and Design in Julia: 3. Time Domain Simulations

Tutoriels, Documentation¶

• An Introduction to the Julia Programming Language: Pluto Notebooks for Julia workshop from American Astronomical Society’s winter meeting.

A bientôt

Pierre

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